A signal model and weighted-average based estimation techniques are proposed to estimate the angle-of-arrival (AOA) parameters of multiple clusters for a low data rate ultrawide band (LR-UWB) based wireless positioning system. The optimal AOA estimation techniques for the LR-UWB wireless positioning system according to the cluster condition are introduced and it is shown that the proposed techniques are superior to the conventional technique from the standpoint of performance.

In off-line analysis, the demand for high precision signal processing has introduced a new method called Empirical Mode Decomposition (EMD), which is used for analyzing a complex set of data. Unfortunately, EMD is highly compute-intensive. In this paper, we show parallel implementation of Empirical Mode Decomposition on a GPU. We propose the use of “partial+total” switching method to increase performance while keeping the precision. We also focused on reducing the computation complexity in the above method from O(N) on a single CPU to O(N/P log (N)) on a GPU. Evaluation results show our single GPU implementation using Tesla C2050 (Fermi architecture) achieves a 29.9x speedup partially, and a 11.8x speedup totally when compared to a single Intel dual core CPU.

A carbonaceous thin film was deposited on a tungsten single emitter by electrolysis of liquid methanol. The carbonaceous single emitter was thermally treated under vacuum conditions, and changes in its field emission characteristics were examined. The field emission characteristics obeyed the Fowler–Nordheim relationship for all annealing temperatures. The turn-on voltage decreased from 1640 V to 790 V with annealing up to 1373 K.

We propose a high-speed and low-complexity architecture for the very large-scale integration (VLSI) implementation of the maximum a posteriori probability (MAP) algorithm suited to the double binary turbo decoder. For this purpose, equation manipulations on the conventional Linear-Log-MAP algorithm and architectural optimization are proposed. It is shown by synthesized simulations that the proposed architecture improves speed, area and power compared with the state-of-the-art Linear-Log-MAP architecture. It is also observed that the proposed architecture shows good overall performance in terms of error correction capability as well as decoder hardware's speed, complexity and throughput.

This paper presents a novel method for reconstructing 3D geometry of camera motion and human-face model from a video sequence. The approach combines the concepts of Powell's line minimization with gradient descent. We adapted the line minimization with bracketing used in Powell's minimization to our method. However, instead of bracketing and searching deep down a direction for the minimum point along that direction as done in their line minimization, we achieve minimization by bracketing and searching for the direction in the bracket which provides a lower energy than the previous iteration. Thus, we do not need a large memory as required by Powell's algorithm. The approach to moving in a better direction is similar to classical gradient descent except that the derivative calculation and a good starting point are not needed. The system's constraints are also used to control the bracketing direction. The reconstructed solution is further improved using the Levenberg Marquardt algorithm. No average face model or known-coordinate markers are needed. Feature points defining the human face are tracked using the active appearance model. Occluded points, even in the case of self occlusion, do not pose a problem. The reconstructed space is normalized where the origin can be arbitrarily placed. To use the obtained reconstruction, one can rescale the computed volume to a known scale and transform the coordinate system to any other desired coordinates. This is relatively easy since the 3D geometry of the facial points and the camera parameters of all frames are explicitly computed. Robustness to noise and lens distortion, and 3D accuracy are also demonstrated. All experiments were conducted with an off-the-shelf digital camera carried by a person walking without using any dolly to demonstrate the robustness and practicality of the method. Our method does not require a large memory or the use of any particular, expensive equipment.

Recently, a number of location-based services such as navigation and mobile advertising have been proposed. Such services require real-time user positions. Since a global positioning system (GPS), which is one of the most well-known techniques for real-time positioning, is unsuitable for indoor uses due to unavailability of GPS signals, many indoor positioning systems (IPSs) using WLAN, radio frequency identification tags, and so forth have been proposed. However, most of them suffer from high installation costs. In this paper, we propose a novel IPS for real-time positioning that utilizes a digital audio watermarking technique. The proposed IPS first embeds watermarks into an audio signal to generate watermarked signals, each of which is then emitted from a corresponding speaker installed in a target environment. A user of the proposed IPS receives the watermarked signals with a mobile device equipped with a microphone, and the watermarks are detected in the received signal. For positioning, we model various effects upon watermarks due to propagation in the air, i.e., delays, attenuation, and diffraction. The model enables the proposed IPS to accurately locate the user based on the watermarks detected in the received signal. The proposed IPS can be easily deployed with a low installation cost because the IPS can work with off-the-shelf speakers that have been already installed in most of the indoor environments such as department stores, amusement arcades, and airports. We experimentally evaluate the accuracy of positioning and show that the proposed IPS locates the user in a 6 m by 7.5 m room with root mean squared error of 2.25 m on average. The results also demonstrate the potential capability of real-time positioning with the proposed IPS.

This letter considers a sum-rate maximization problem with user scheduling wherein each user has a minimum-rate requirement in multiple-input-multiple-output broadcast channel. The multiuser strategy used in the user scheduling is a joint transceiver scheme with block diagonal geometric mean decomposition. Since optimum solution to the user scheduling problem generally requires exhaustive search, we propose a suboptimum user scheduling algorithm with each user's minimum-rate requirement as the main constraint. In order to satisfy maximum sum-rate and minimum-rate constraints simultaneously, we additionally consider power allocation for scheduled users. Simulation results show that the proposed user scheduling algorithm, together with the user power allocation, achieves sum-rate close to the exhaustive search, while also guarantees minimum-rate requirement of each user.

This paper proposes a method for setting the threshold for ultra-wide-band (UWB) threshold-based ranging in indoor scenarios. The optimum threshold is derived based on the full analysis of the ranging error, which is equivalent to the probability of correct detection of first arriving signal in time-based ranging techniques. It is shown that the probability of correct detection is a function of first arriving signal, which has variations with two independent distributions. On the one hand, the first arriving signal varies in different positions with the same range due to multipath interference and on the other, it is a function of distance due to free space path-loss. These two distributions are considered in the derivation of the ranging error, based on which the optimum threshold is obtained. A practical method to derive this threshold is introduced based on the standard channel model. Extensive Monte Carlo simulations, ray-tracing simulations and ranging measurements confirm the analysis and the superior performance of the proposed threshold scheme.

In this letter, a prerake combining scheme for signal detection in ultra-wideband (UWB) multiple input single output (MISO) systems with a hybrid pulse amplitude and position modulation (PAPM) is analytically examined. For a UWB MISO system, the analytical BER performance of a prerake combining scheme with PAPM is presented in a log-normal multipath fading channel. The analytical BERs are observed to match well the simulated results for the set of parameters chosen. The prerake diversity combining UWB systems, which can significantly reduce the complexity of the receiver side compared to the rake diversity systems, improve the error performance as the number of transmit antennas increases.

A reliable antifuse scheme has been very hard to build, which has precluded its implementation in DRAM products. We devised a very reliable multi-cell structure to cope with the large process variation in the DRAM-cell-capacitor type antifuse system. The programming current did not rise above 564 µA even in the nine-cell case. The cumulative distribution of the successful rupture in the multi-cell structure could be curtailed dramatically to less than 15% of the single-cell's case and the recovery problem of programmed cells after the thermal stress (300) had disappeared. In addition, we also presented a Post-Package Repair (PPR) scheme that could be directly coupled to the external high-voltage power rail via an additional pin with small protection circuits, saving the chip area otherwise consumed by the internal pump circuitry. A 1 Gbit DDR SDRAM was fabricated using Samsung's advanced 50 nm DRAM technology, successfully proving the feasibility of the proposed antifuse system implemented in it.

We consider how to accurately estimate the position of targets that exist in closed areas such as a room. In the past, arranging the sensors in a straight line would trigger large position estimation errors in the same direction of the straight line. However, this arrangement is useful because of easy setting, wirings, and space limitations. In this paper, we show a novel algorithm which can reduce the error using signals from reflection objects such as walls. The algorithm uses ellipse relations among sensors, targets and reflection points. Using ellipse relations, the algorithm estimates the positions of the reflection points which are assumed to be the locations of the virtual sensors. So in spite of the straight sensor arranging, the sensors are virtually distributed such as surrounding the targets. In this paper, we show the algorithm and error reduction performances as determined from computer simulations.

One of the efficient methods to build the index of continuous window queries over moving objects is by means of region quadtree index. In this paper, we present an optimal algorithm to search for the optimal position translation of query windows, where the total number of decomposed quadtree blocks for those windows in quadtree representation is minimal. We exploit the branch-and-bound concept to prune the particular paths of recursions in the search space. Evaluation proves that our optimal algorithm reduces search time greatly and the quadtree index based on optimal position translation works efficiently for continuous window queries. To the best of our knowledge, the algorithms and experiments reported in this paper are novel.

In this paper, we propose a Network Knowledge Layer (NKL) that is a service platform overlaid onto the existing networks to provide network knowledge for user-centric services in the Next Generation Network (NGN). Most traditional networks lack capabilities for accommodating user-centric service paradigm. Taking this into consideration, the proposed NKL has capabilities to acquire contextual information from various sources, to evolve this information with legacy information into high-level knowledge, and to expose the high-level knowledge to entities outside the network. For easy knowledge exposure, we specify a set of abstracted application programming interfaces (APIs). For efficient handling of network knowledge accessed by the APIs, we design and compare the three different network knowledge models. With the proposed APIs and the three knowledge models, we accomplish the experimental performance evaluation of NKL to verify its feasibility. The results of the various tests on knowledge models and APIs give good guidelines for efficient design and exposing network knowledge in developing a user-centric service platform. Finally, we expect NKL can support the effective development and execution of user-centric services by providing rich network knowledge with the APIs.

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, lower multi-path distortion and others. To further utilize the vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subcarrier and bit allocation among users. In this paper, we propose a 0-1 integer programming model formulating the optimal subcarrier and bit allocation problem of the multiuser OFDM. We proved that the continuous relaxation of our formulation is tighter than the previous convex optimization formulation based on perspective function and the Lagrangian dual bound of our formulation is equivalent to the linear programming relaxation bound. The proposed Lagrangian dual is seperable with respect to subcarriers and allows an efficient dual maximization algorithm. We compared the performance of the integer programming formulation and the Lagrangian dual of our formulation and the continuous relaxation and the primal heuristic proposed in [3]. Computer simulation on a system employing M-ary quadrature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multipaths is carried out with the optimal subcarrier and bit allocation solution generated by the 0-1 integer programming model.

In this paper, we present an approach of detecting speech presence for which the decision rule is based on a combination of multiple features using a sigmoid function. A minimum classification error (MCE) training is used to update the weights adjustment for the combination. The features, consisting of three parameters: the ratio of ZCR, the spectral energy, and spectral entropy, are combined linearly with weights derived from the sub-band domain. First, the Bark-scale wavelet decomposition (BSWD) is used to split the input speech into 24 critical sub-bands. Next, the feature parameters are derived from the selected frequency sub-band to form robust voice feature parameters. In order to discard the seriously corrupted frequency sub-band, a strategy of adaptive frequency sub-band extraction (AFSE) dependant on the sub-band SNR is then applied to only the frequency sub-band used. Finally, these three feature parameters, which only consider the useful sub-band, are combined through a sigmoid type function incorporating optimal weights based on MSE training to detect either a speech present frame or a speech absent frame. Experimental results show that the performance of the proposed algorithm is superior to the standard methods such as G.729B and AMR2.

In this paper a third-order inter-modulation cancellation technique using Pre-Post-Distortion is proposed to design a wideband high linear low-power LNA in deep submicron. The IM3 cancellation is achieved by post-distorting signal inversely after it is pre- distorted in the input trans-conductance stage during amplification process. The operating frequency range of the LNA is 800 MHz–5 GHz. The proposed technique increases input-referred third-order intercept point (IIP3) and input 1 dB Compression point (P-1 dB) to 12–25 dBm and -1.18 dBm, respectively. Post layout simulation results show a noise figure (NF) of 4.1–4.5 dB, gain of 13.7–13.9 dB and S11 lower than -13 dB while consumes 8 mA from 1.2 V supply. The LNA is designed in a 65 nm standard CMOS technology. The layout schematic shows that the LNA occupies 0.150.11 mm2 of silicon area.

We consider a queuing model with applications to electric vehicle (EV) charging systems in smart grids. We adopt a scheme where an Electric Service Company (ESCo) broadcasts a one bit signal to EVs, possibly indicating 'on-peak' periods during which electricity cost is high. EVs randomly suspend/resume charging based on the signal. To model the dynamics of EVs we propose an M/M/∞ queue with random interruptions, and analyze the dynamics using time-scale decomposition. There exists a trade-off: one may postpone charging activity to 'off-peak' periods during which electricity cost is cheaper, however this incurs extra delay in completion of charging. Using our model we characterize achievable trade-offs between the mean cost and delay perceived by users. Next we consider a scenario where EVs respond to the signal based on the individual loads. Simulation results show that peak electricity demand can be reduced if EVs carrying higher loads are less sensitive to the signal.

This paper presents a new low-dropout (LDO) regulator with low-quiescent, high-drive and fast-transient performance. This is based on a new composite power transistor composed of a shunt feedback class-AB embedded gain stage and the application of dynamic-biasing schemes to both the error amplifier as well as the composite power transistor. The proposed LDO regulator has been simulated and validated using BSIM3 models and GLOBALFOUNDRIES 0.18-µm CMOS process. The simulation results have shown that the LDO regulator consumes 4.7 µA quiescent current at no load, regulating the output at 1 V from a minimum 1.2 V supply. It is able to deliver up to 450 mA load current with a dropout of 200 mV. It can be stabilized using a 4.7 µF output capacitor with a 0.1 Ω ESR resistor. The maximum transient output voltage is 64.6 mV on the basis of a load step change of 450 mA/10 ns under typical condition. The full load transient response is less than 350 ns.

DV-Hop algorithm produces errors in location estimations due to inaccurate hop size. We propose a novel localization scheme based on DV-Hop to improve positioning accuracy with least error hop sizes of anchors and average hop sizes of unknowns. The least error hop size of an anchor minimizes its location error, but it may be far small or large. To cope with this inconsistent hop size, each unknown node calculates its average hop size with hop sizes from anchors. Simulation results show that the proposed algorithm outperforms the DV-Hop algorithm in location estimations.

Post-silicon debugging is getting even more critical to shorten the time-to-market than ever, as many more bugs escape pre-silicon verification according to the increasing design scale and complexity. Post-silicon debugging is generally harder than pre-silicon debugging due to the limited observability and controllability of internal signal values. Conventionally, simulation of corresponding low-level designs such as RTL or gate-level has been used to get observability and controllability, which is inefficient for contemporary large designs. In this paper, we introduce a post-silicon debugging approach using simulation of high-level designs, instead of low-level designs. To realize such a debugging approach, we propose an I/O sequence mapping method that converts I/O sequences of chip executions to those of the corresponding high-level design. First, we provide a formal definition of I/O sequence mapping and relevant notions. Then, based on the definition, we propose an I/O sequence mapping method by executing FSMs representing the interface specifications of the target design. Also, we propose an implementation of the proposed method to get further efficiency. We demonstrate that the proposed method can be effectively applied to several practical design examples with various interfaces.